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Figurative language, such as metaphor, metonymy, idioms, among others, is in abundance in natural discourse. The recognition of figurative language use and the computation of figurative language meaning constitute one of the hardest problems for a variety of natural language processing tasks, such as machine translation, text summarization, and question answering. As natural language processing moves to an unprecedented new stage, it has become more urgent than ever to tackle the bottleneck presented by figurative language.

This workshop will provide a venue for researchers in this area to inform each other and the natural language processing community at large of the state of the art of current systems and to reach a better understanding of the new issues and challenges that need to be tackled. This workshop will be held in conjunction with HLT/NAACL 2007.

Computational Approaches to Figurative Language

Workshop in conjunction with HLT/NAACL 2007 To be held in Rochester, NY, April 26, 2007

Figurative language, such as metaphor, metonymy, idioms, personification, simile among others, is in abundance in natural discourse. It is an effective apparatus to heighten effect and convey various meanings, such as humor, irony, sarcasm, affection, etc. Figurative language can be found not only in fiction, but also in everyday speech, newspaper articles, research papers, and even technical reports. The recognition of figurative language use and the computation of figurative language meaning constitute one of the hardest problems for a variety of natural language processing tasks, such as machine translation, text summarization, information retrieval, and question answering. Resolution of this problem involves both a solid understanding of the distinction between literal and non-literal language and the development of effective computational models that can make the appropriate semantic interpretation automatically.

As natural language processing moves to an unprecedented new stage, it has become more urgent than ever to tackle the bottleneck presented by figurative language. There has been an increasing amount of work in this area in the past few years (e.g. theoretical semantic/pragmatic analyses of non-compositional phenomena, research on psychological/neuro-linguistic modeling of figurative language comprehension and production, research on the structure of the lexicon, knowledge representation and figurative language comprehension, domain-specific figurative language detection, computational corpus studies of figurative language), but much more work needs to be done (e.g. large-scale automatic figurative language detection, automatic extraction of idioms and non-compositional phrases from large corpora, automatic semantic interpretation of figurative language, automatic figurative language generation, machine translation of non-literal phenomena, etc.). The goal of this workshop is to provide a venue for researchers in this area to inform each other and the natural language processing community at large of the state of the art of current systems and to reach a better understanding of the new issues and challenges that need to be tackled.

The workshop is intended to be highly interdisciplinary. We encourage the participation of people whose research deals with figurative language from different perspectives, including (but not limited to) applied linguistics, psychology, corpus linguistics, human-computer interaction, natural language processing, etc.

(4) Theoretical discussions on literal and non-literal language, including discussions on - the distinction between literal and non-literal language - the distinction between different types of figurative language - cross-linguistic differences of figurative language

(5) Lexical and ontological resources for figurative language processing, including - representation of non-literal meaning in lexicons and ontologies - development of new lexical resources for figurative language processing

The emphasis of the workshop is on computational approaches to figurative language. We particularly are interested in submissions that deal with figurative language in the context of Machine Translation, Word Sense Disambiguation, Information Extraction, Document Retrieval, Dialogue Systems, Intelligent Tutoring systems, etc.

Chris Brew, The Ohio State University Afsaneh Fazly, University of Toronto, Canada Eileen Fitzpatrick, Montclair State University Sam Glucksberg, Princeton University Sid Horton, Northwestern University Diana Inkpen, University of Ottawa, Canada Kevin Knight, USC/Information Sciences Institute Mark Lee, The University of Birmingham, UK Katja Markert,University of Leeds, UK Detmar Meurers, The Ohio State University Rada Mihalcea, University of North Texas Andrew Ortony, Northwestern University Wim Peters, University of Sheffield, UK Vasile Rus, The University of Memphis Richard Sproat, University of Illinois at Urbana-Champain Suzanne Stevenson, University of Toronto, Canada Carlo Strapparava, Istituto per la Ricerca Scientifica e Tecnologica, Trento, Italy